Session Detail

This study presents a rapid diagnostic for mycobacterial tuberculosis (MTB) infection by measuring mycobacterial enzyme activity. Detection of the enzyme activity is tantamount to the presence and activity of bacterial cells. Mycobacterial topoisomerase (MTop), a significant enzyme in the proliferation of the bacteria, can partially break the supercoiled double stranded DNA helix to relax and then reanneal afterwards. Here we present a nano-sensor for detecting mycobacterial viability based on its topoisomerase enzymes' cleavage activities against the mycobacterial DNA substrates embedded in our microchannels. The nano-sensor comprises a carrier particle (dp=50 μm) conjugated with gold nanoparticles (AuNPs) via designed DNA strands. Liquid samples containing the pathogenic microbial topoisomerase enzymes are allowed to run along our fabricated borosilicate glass microchannel driven by capillary force. Embedded at the middle of the microchannels are obstacles for the carrier particles but will allow other small particles (AuNPs and proteins) to pass. When the MTopI enzymes are active, the carrier particles and AuNPs are separated because the linker DNAs are cleaved. As a result, AuNPs are washed away from the microchannels. Conversely, the nano-sensors conjugated with AuNPs tend to aggregate in the front end of the obstacles, resulting in visible red color band in the microchannel. Figure 3 illustrates fluid flow of the MTopI sample and the DNA nano-sensors along the microchannel driven by capillary force starting from the inlet towards the end of the channel. In summary, we proposed an integrated platform combining the DNA nano-sensors, capillary force, and colorimetry to address current challenges in rapid MTB diagnosis with high sensitivity and specificity through the measurement of MTopI enzyme cleavage activities.

 

The proof of concept of utilizing a microfluidic dielectrophoresis (DEP) chip was conducted to rapidly detect a dengue virus (DENV) in vitro based on the fluorescence im-munosensing. The mechanism of detection was that the DEP force was employed to capture the modified beads (mouse anti-flavivirus monoclonal antibody-coated beads) in the microflu-idic chip and the DENV modified with fluorescence label, as the detection target, can be then captured on the modified beads by immunoreaction. The fluorescent signal was then obtained through fluorescence microscopy, and then quanti-fied by ImageJ freeware. The platform can accelerate an im-munoreaction time, in which the on-chip detection time was 5 min, and demonstrating an ability for DENV detection as low as 104 PFU/mL. Furthermore, the required volume of DENV samples dramatically reduced, from the commonly used ~50 μL to ~15 μL, and the chip was reusable ( > 50x). Overall, this platform provides a rapid detection (5 min) of the DENV with a low sample volume, compared to conventional methods. This proof of concept with regard to a microfluidic dielectrophore-sis chip thus shows the potential of immunofluorescence based-assay applications to meet diagnostic needs.The proof of concept of utilizing a microfluidic dielectrophoresis (DEP) chip was conducted to rapidly detect a dengue virus (DENV) in vitro based on the fluorescence im-munosensing. The mechanism of detection was that the DEP force was employed to capture the modified beads (mouse anti-flavivirus monoclonal antibody-coated beads) in the microflu-idic chip and the DENV modified with fluorescence label, as the detection target, can be then captured on the modified beads by immunoreaction. The fluorescent signal was then obtained through fluorescence microscopy, and then quanti-fied by ImageJ freeware. The platform can accelerate an im-munoreaction time, in which the on-chip detection time was 5 min, and demonstrating an ability for DENV detection as low as 104 PFU/mL. Furthermore, the required volume of DENV samples dramatically reduced, from the commonly used ~50 μL to ~15 μL, and the chip was reusable ( > 50x). Overall, this platform provides a rapid detection (5 min) of the DENV with a low sample volume, compared to conventional methods. This proof of concept with regard to a microfluidic dielectrophore-sis chip thus shows the potential of immunofluorescence based-assay applications to meet diagnostic needs.

 

This work developed a cost-efficient and portable electroencephalogram (EEG) acquisition platform by entirely leveraging off-the-shelf electronic components/modules and dry electrodes. The dry electrodes were placed on a 3D-printed soft electrode holder that allows self-assembly by a user regarding the number and location of electrodes to be placed for the cognitive task of interest. By conducting an event-related potential (ERP) experiment namely Go/Nogo task, the obtained ERP outcome of salient fronto-central N2 and P3 peaks accompanied by only inhibitory responses empirically demonstrated the integrity of the platform in terms of signal quality and data synchronization.

 

Medical interventional devices (MIDs) are commonly used to provide access for minimally invasive diagnosis. In this study, We propose the very advanced technique for studying medical interventional devices (MID) with soft tissue interaction by extracting acoustic emission data from the proximal end of the MID. We have to extract dynamical characteristics of the interaction between the MID distal tip and soft tissue. We found that signal which has less noise, confirms the right placement of the device in the soft tissue. This study shows a novel method to obtain valuable information for MID guidance and tissue/device interactions for further analysis and evaluation.

 

The shoulder joint is the joint with the largest range of human activity, and it is easy to cause rotator cuff tendons to inflammation, wear and even breakage. At present, the main treatment of shoulder joint surgery is shoulder arthroscopy. Arthroscopic surgery is mainly direct observation of the patient’s shoulder joint by arthroscope through the muscles, and then the physician uses surgical instruments to give the treatment through another hole of muscle. However, in the process of shoulder arthroscopy, fluid injection is often required, because the tissue shaved through the device will constantly interfere with the visual field in the picture, so the doctor usually uses fluid injection to maintain the clarity of the picture but they cannot adjust the amount of injection well. In view of this, patient's shoulder would have postoperative edema after surgery owing to the improper fluid injection. Besides, the excessive injection can even lead to severe respiratory disease or PAGCL [1]. Therefore, this study intends to develop the algorithm of automatic irrigation pump by using the artificial intelligence. The images of the shoulder arthroscopy are provided by Cheng Kung University Hospital, and we try to input the testing image into the trained classifier to help determine whether the view of shoulder arthroscopy picture is clear enough and the classification result is given as the reference of the automatic irrigation pump for fluid injection. This study uses the mainstream con-volutional neural network: Alexnet as a tool, and also tests and evaluates the feasibility of artificial intelligence for differentiating different condition of fluid injection. We expect that our training model can be used as the algorithm for automatic irrigation pump and make the patient recover much better in the future.